A number of systems and programs are offered on the market for the design, the engineering and the manufacturing of objects. CAD is an acronym for Computer-Aided Design, e.g. it relates to software solutions for designing an object. CAE is an acronym for Computer-Aided Engineering, e.g. it relates to software solutions for simulating the physical behavior of a future product. CAM is an acronym for Computer-Aided Manufacturing, e.g. it relates to software solutions for defining manufacturing processes and operations. In such computer-aided design systems, the graphical user interface plays an important role as regards the efficiency of the technique. These techniques may be embedded within Product Lifecycle Management (PLM) systems. PLM refers to a business strategy that helps companies to share product data, apply common processes, and leverage corporate knowledge for the development of products from conception to the end of their life, across the concept of extended enterprise. The PLM solutions provided by Dassault Systèmes (under the trademarks CATIA, ENOVIA and DELMIA) provide an Engineering Hub, which organizes product engineering knowledge, a Manufacturing Hub, which manages manufacturing engineering knowledge, and an Enterprise Hub which enables enterprise integrations and connections into both the Engineering and Manufacturing Hubs. All together the system delivers an open object model linking products, processes, resources to enable dynamic, knowledge-based product creation and decision support that drives optimized product definition, manufacturing preparation, production and service.
In this framework, depth sensors are currently involved in many applications such as 3D reconstruction, Augmented Reality, Human-Computer Interface and Video Games. Depth sensors provide depth information in real-time and at high frame rates. Main existing depth sensor technologies include Time of Flight (ToF) depth sensors and Structured Light (SL) depth sensors.
Time of Flight depth sensors measure the time-of-flight a light signal takes between the camera and the subject. This gives the depth of the subject at that point. These sensors are based on the emission of a modulated infrared light which is thereafter reflected by the objects in the scene. The signal's phase shift φ is determined and thus the depth is computed by
      Z    =                  c        ⁢                                  ⁢        φ                    4        ⁢        πω              ,where c is the speed of light and ω is the modulation frequency.
Structured Light depth sensors have one camera and one laser-based IR projector which form a stereo pair. The IR projector sends out a fixed grid light pattern on the subject which gives a distorted version of this grid, captured with the infrared camera. Depth is calculated by triangulating the distorted grid against the exact grid. For a new image, one wants to calculate the depth at each pixel. For each pixel in the IR image, a small correlation window (9×9 or 9×7) is used to compare the local pattern at that pixel with the memorized pattern at that pixel and 64 neighboring pixels in a horizontal window. The best match gives an offset from the known depth. In terms of pixels this is called disparity. Thus the depth is computed by
  Z  =      bf    d  where Z is the depth (in meters), b is the horizontal baseline between the camera and the projector (in meters), f is the focal length of the cameras (in pixels), and d is the disparity (in pixels).
While the low cost and ease of use of these sensors is highly appreciated, they suffer from a high level of noise. Some work has been devoted to improve this issue, for example by means of filtering/denoising technics applied to the noisy depth measurements, but at the time being no noiseless depth sensor is known.
Within this context, there is still a need for an improved solution with respect to the noise in measurements performed by depth sensors.